Episodes
Why Attribution Models Miss Co-Branded Card Spending
In this episode of Marketing Analytics, hosts Lucas and Luna dive into a blind spot in attribution: co-branded credit card spend. They break down why standard models treat card swipes as untrackable and how that inflates the credit given to the last click or the card network. Using a concrete example of an airline co-brand card, they show how the real driver is an existing relationship, not a digital ad, and why every co-brand deal should come with its own attribution language. They also touch…
Why Attribution Models Ignore Sales Team Input
In this episode of Marketing Analytics, Lucas and Luna explore a blind spot in most attribution models: the sales team. When a prospect talks to a sales rep before converting, the marketing touchpoints that actually influenced the decision often get zero credit. Lucas walks through a concrete example from B2B software, where a whitepaper download and a demo request both preceded a sales call, yet the attribution model—set to last-click—credited only the sales follow-up email. They discuss why…
Why Attribution Models Miss the Value of Customer Communities
Episode 160 of Marketing Analytics with Fexingo digs into a blind spot in most attribution models: customer communities. Lucas and Luna explore how forums, Slack groups, and user-generated Q&A threads drive purchases in ways that last-click and even multi-touch models fail to credit. They look at concrete examples — a B2B software company where community-sourced answers shortened sales cycles, and an outdoor gear brand whose user forum lifted repeat purchases — and break down why communities…
Why Attribution Models Miss the Value of Customer Education
Lucas and Luna dig into a blind spot in most marketing attribution models: customer education. They explore how webinars, help-center articles, and product tutorials drive conversions without ever getting credit. Using a durable example like HubSpot's academy and a fictional software company's demo sign-ups, they walk through why last-click and even multi-touch models undervalue the assist. They also get practical: how to set up a simple UTM strategy for educational content and how to use…
How Marketing Attribution Misses the Value of Free Trials
Free trials are a staple of SaaS growth, but most attribution models misread them. In this episode, Lucas and Luna dig into why the trial period is an attribution blind spot: does the credit go to the click that started the trial, the email that nudged conversion, or the product experience itself? They walk through a concrete example, how different attribution windows change the story, and why the real value of a trial often sits outside the last-click tunnel. If you've ever wondered why your…
Why Attribution Models Miss Podcast Host-Read Ads
On this episode of Marketing Analytics with Fexingo, Lucas and Luna dig into why podcast host-read ads stubbornly escape most attribution models. They walk through a real-world example: a DTC skincare brand that saw a noticeable sales bump after a podcast campaign, yet its analytics platform credited almost nothing to the podcast. They break down the three core problems — no clickable link, delayed listening, and promo-code friction — and explain what marketers can actually do about it, from…
Why Attribution Models Miss the Value of Customer Lifetime Value
In this episode of Marketing Analytics, Lucas and Luna explore a blind spot in most attribution models: they optimize for the conversion, not the customer. Using the example of a subscription meal-kit company, they show how last-click and even multi-touch models undervalue the first purchase, which is often driven by a discount, and overvalue the repeat orders that come from habit. They discuss how shifting to a customer lifetime value (CLV) framework changes budget allocation, creative…
How Attribution Models Miss the Value of Product Returns
Returns are a marketer's blind spot. In this episode, Lucas and Luna dig into why your attribution model treats a product return as a cost line, not a signal. They walk through the data problem: returns get logged in a fulfillment system, never synced to the CRM, so the marketing platform sees a completed order and credits the wrong channel. They cite a real-world stat — return rates run 20 to 40 percent for fashion e-commerce — and unpack what happens when you actually feed returns back into…
Why Attribution Models Miss the Value of Referral Partners
In this episode of Marketing Analytics, Lucas and Luna examine a blind spot in most attribution models: referral partners. They break down why a fitness equipment brand's partnership program kept driving sales that standard last-click models credited entirely to paid search. Using this case, they explain how multi-touch attribution and incrementality testing can reveal the true value of partner referrals, and why ignoring them leads to misallocated budgets and missed growth. The conversation…
Why Marketing Attribution Misses the Value of Customer Success
In this episode of Marketing Analytics, Lucas and Luna tackle a blind spot in attribution: customer success interactions. They explore how onboarding calls, support tickets, and success check-ins often get zero credit in marketing dashboards, even though they compound the effect of every campaign. Using a fictional SaaS example and a real-world analogy to a car dealership's service lane, they explain why post-purchase touchpoints distort both marketing and retention metrics. They discuss how to…
How Attribution Models Miss Store Pickup Orders
Buy online, pick up in store — BOPIS — is a huge chunk of retail revenue now, yet most attribution models still credit the online click and ignore the physical store visit that completes the sale. In this episode, Lucas and Luna dig into why that mis-crediting happens, how it inflates digital ROI numbers, and what it does to in-store staffing and inventory decisions. They walk through a concrete example: a $75 order where the last-click model gives 100% credit to paid search, even though the…
Why Attribution Models Miss Loyalty Program Signups
Lucas and Luna explore why marketing attribution models often fail to credit loyalty program signups, even when they drive significant customer lifetime value. They break down the mechanics of how loyalty programs create a measurement blind spot—because signups happen in-store, on apps, or via customer service, while the eventual purchases get attributed to other channels. The episode centers on a pharmacy chain that launched a coffee loyalty program and saw a measurable lift in cross-category…
How Marketing Attribution Fails to Credit Bundled Products
In episode 150 of Marketing Analytics with Fexingo, Lucas and Luna explore a blind spot in attribution: when customers buy bundles, like a phone with a free earbud, the model can't decide which product gets credit. Using the example of a consumer electronics brand offering a 'buy one, get one' promotion, they show how multi-touch models mishandle bundle economics, why last-click defaults to the higher-priced item, and how order-level attribution can distort product-level ROI. Lucas explains how…
Why Attribution Models Miss the Value of Branded Search
In this episode of Marketing Analytics with Fexingo, Lucas and Luna explore why attribution models consistently undervalue branded search. Using the example of a DTC skincare company that saw a 40 percent drop in branded search volume after pausing TV ads, they explain how last-click and multi-touch models misattribute branded search to organic or direct traffic, leading to underinvestment in the very campaigns that drive it. They discuss the concept of 'branded search lift' and how brands can…
Why Attribution Models Miss Retail Media Networks
Retail media networks are reshaping digital advertising, but most attribution models still treat them like ordinary display ads. In this episode, Lucas and Luna break down why that's a problem, using a concrete example from a major grocery chain's sponsored product results. They explain how retail media networks capture shopper intent, why last-click attribution undercounts their role, and what marketers can do about it—including testing with geo experiments and building incrementality into…
Why Attribution Models Ignore Missed Calls
In this episode of Marketing Analytics with Fexingo, Lucas and Luna dig into a blind spot that trips up even sophisticated attribution setups: the missed call. They unpack why offline conversions like phone calls are systematically under-measured, how call tracking platforms fill the gap, and why businesses that rely on high-ticket sales or local services often see a huge jump in measured ROI once calls are added to the model. Using a concrete example—a plumbing company that discovered 40…
Why Your Attribution Model Misses QR Codes
Lucas and Luna dig into a blind spot in marketing attribution: QR codes. While QR codes have become a standard bridge between offline and online worlds, most attribution models either ignore them entirely or misattribute their impact to the next click. The hosts walk through a concrete example from a restaurant chain that printed QR codes on table tents, only to see the traffic credited to direct or organic search. They explain why QR codes fall through the cracks, from cookie deprecation to…
Why Attribution Overcredits Coupon Code Last Clicks
Coupon codes are the cleanest conversion signal an attribution model can see — which is exactly why they hog credit. In this episode, Lucas and Luna dig into the perverse incentive: every deal code a customer types is recorded as a last-click win, while the search ads, podcasts, and out-of-home placements that built the demand get nothing. They walk through a real mid-size DTC brand's numbers: 38 percent of orders carrying a code, but the codes themselves only arriving in email and paid search.…
Why Podcast Ads Escape Your Attribution Model
Podcast advertising hit $4 billion in 2025, but most marketing attribution models can't track a single dollar of it. Lucas and Luna dive into the structural reasons: dynamic ad insertion, host-read authenticity, lack of clickable links, and the reliance on promo codes and surveys. They explore why last-click fails, how brand lift studies work for audio, and what marketers can do to measure podcast ROI better. A must-listen for anyone running or analyzing audio campaigns. #MarketingAnalytics…
How Marketing Attribution Misses In-Game Ads
In-game advertising is projected to top $10 billion in 2026, but standard attribution models ignore it because many ads are non-clickable rewarded videos or playables. Lucas and Luna explain why last-click models fail, how walled gardens like Unity Ads fragment measurement, and what marketers can do—from geo lift studies to SDK-based tracking. They discuss a snack brand case study showing a 12% lift in purchase intent with zero credit from traditional attribution, and highlight IAB measurement…
Why Your Attribution Model Ignores Internal Site Search
Episode 142 of Marketing Analytics with Fexingo uncovers a blind spot in most attribution models: internal site search. Lucas and Luna explain why search queries on your own site are invisible to standard attribution, even though they signal high intent—converting at nearly double the average rate. They walk through the technical reasons (cookie gaps, session fragmentation, missing touchpoints) and share how a D2C mattress brand fixed it by tracking search terms as touchpoints, boosting ROAS by…
Why Attribution Models Miss Customer Reviews
In this episode of Marketing Analytics with Fexingo, Lucas and Luna explore a persistent blind spot in marketing measurement: the influence of customer reviews and ratings. Despite research showing that a one-star increase on a product page can lift conversion rates by 20 percent, most attribution models assign zero credit to that review. They discuss why this happens, how review-driven purchases break standard tracking, and what marketers can do to start measuring the impact—including using…
Why Paid Search Attribution Misses Organic Lift
In this episode of Marketing Analytics with Fexingo, Lucas and Luna dive into a persistent attribution blind spot: the hidden synergy between paid search and organic conversions. Using a real retailer case where pausing non-branded paid ads caused a 15% drop in organic conversion rates, they explain why last-click models undervalue paid search, how Google's search results page creates a compound effect, and what marketers can do instead—from geo-lift experiments to time-decay attribution. If…
How Apple's ATT Broke Facebook Attribution Models
In this episode of Marketing Analytics with Fexingo, Lucas and Luna explore the seismic impact of Apple's App Tracking Transparency on Facebook ad attribution. Using a real-world DTC skincare brand as a case study—where attributed Facebook conversions dropped from 60% to under 20% post-ATT—they unpack how attribution models became unreliable when data sources changed. They discuss why many advertisers saw inflated ROAS from Facebook's modeled conversions, the critical need for incrementality…
How Influencer Marketing Breaks Your Attribution Model
In this episode of Marketing Analytics with Fexingo, Lucas and Luna drill into one of the stickiest attribution problems facing brands today: influencer marketing. Most attribution models last-click to a direct link or a promo code, but a 2025 eMarketer study found that nearly 70 percent of influencer-driven conversions happen outside that window—through later search, direct visits, or offline word-of-mouth. Lucas walks through a real case: a DTC skincare brand that saw a 40 percent revenue…
Why Your Attribution Model Ignores Out-of-Home Ads
Billboards and transit ads are the last attribution blind spot. In this episode, Lucas and Luna dig into why out-of-home advertising rarely gets credit in multi-touch models, using the example of a national quick-service restaurant that ran a $2 million billboard campaign across three DMAs. They explore how mobile location data, geo-lift experiments, and brand lift surveys are starting to solve the measurement gap—and why most attribution vendors still punt on OOH. #MarketingAnalytics…
Why Referral Traffic Gets Undervalued in Attribution Models
Episode 136 of Marketing Analytics with Fexingo. Lucas and Luna explore why traditional attribution models systematically undercount customer referrals—especially those that happen offline or via untrackable links. Drawing on a 2025 study from the Word of Mouth Marketing Association (WOMMA), which found that referrals drive 18% of new customer acquisitions but only 2% are attributed to a trackable source, the hosts break down the mechanics of refer-a-friend programs, dark referrals, and the…
Why Connected TV Ads Escape Marketing Attribution
In this episode, Lucas and Luna tackle a persistent blind spot in marketing attribution: connected TV (CTV) advertising. Despite surging ad spend—projected at $30 billion in the US by 2026—CTV campaigns often receive zero credit in last-click models because there is no click-through. Lucas shares a case study of a national retailer that ran a four-week CTV campaign across Hulu and YouTube TV, saw a 12% lift in store visits and an 8% lift in branded search, yet its multi-touch attribution tool…
How Brand Advertising Gets Ignored by Attribution Models
In this episode, Lucas and Luna dive into a persistent blind spot in marketing analytics: the systematic undervaluation of brand advertising in attribution models. Citing a recent Analytic Partners study showing brand drives about 60% of sales lift but gets less than 10% credit in standard models, they explore why this gap exists and how it misleads budget allocation. They discuss the measurement challenges—long conversion windows, no click path, offline impact—and offer practical fixes like…
Why Your Attribution Model Overweights Display Retargeting
Lucas and Luna expose a hidden flaw in marketing attribution: display retargeting gets more credit than it deserves because of recency bias, last-click proximity, and inflated view-through conversion windows. Using a real $2 million campaign example from a DTC mattress brand, they explain why retargeting's attributed ROAS can look like 8x when the true incrementality is closer to 1.3x. The hosts walk through a simple geo holdout test and a two-hour time decay adjustment that cut retargeting's…
How Marketing Attribution Misses Dark Social
Lucas and Luna unpack dark social — the private sharing (texts, DMs, emails, WhatsApp) that your attribution model can't see. They discuss a 2025 RadiumOne study showing dark social drives 32% of all content sharing, yet most marketing dashboards assign it zero credit. They walk through real examples: a meal-kit brand that saw 19% more first orders after adding a dark-social survey, and a B2B software company that found 41% of its demo requests came from links pasted into Slack or email. They…
How Marketing Attribution Mistakenly Credits Email Opens
Episode 131 challenges a common assumption in email marketing attribution: that an email open equals genuine influence. Lucas and Luna unpack a 2025 study from Litmus showing that Apple's Mail Privacy Protection causes roughly 60% of tracked 'opens' to be automated, not human. They discuss the impact on click-through rates, conversion data, and how multi-touch models get skewed when email is overweighted. The episode also explores alternative approaches like unique link clicks and server-side…
Why Geo Experiments Beat Multi-Touch Attribution
Lucas and Luna tackle a blind spot that trips up nearly every marketing team: the over-reliance on user-level attribution models that can't capture aggregate effects like brand lift or halo. They break down why the industry is slowly pivoting to geo-based experiments — using real examples from a national retailer that ran a six-week geo test across 40 DMAs. Lucas explains the math behind minimum detectable effect and why most brands run experiments that are too small to trust. Luna challenges…
Why Your Attribution Model Misses Branded Search
Episode 129 of Marketing Analytics with Fexingo. Lucas and Luna dig into a blind spot in most attribution models: branded search. They walk through a real scenario from a mid-market DTC brand that saw its ROAS drop 30% after attributing all branded-search conversions to the last click — even though those searches were triggered by podcast and TV ads weeks earlier. Lucas breaks down the 'branded-search cannibalization' trap, why last-click models overcredit owned channels, and how a simple…
How Marketing Attribution Misses Audio Streaming Ads
Episode 128 of Marketing Analytics with Fexingo. Lucas and Luna tackle a blind spot in attribution: streaming audio ads on Spotify and Apple Music. Most marketers still use click-based tracking for a channel that has near-zero click-through rates. Lucas breaks down how Spotify's streaming ad insertion works, why last-click attribution assigns zero credit, and how brands like HelloFresh and Squarespace actually measure incrementality through promo codes and brand-lift studies. Luna pushes back…
Why Your Attribution Model Ignores Call Extensions
Episode 127 of Marketing Analytics with Fexingo dives into a blind spot many attribution models share: phone calls. While Clicks and form fills get tracked down to the keyword, phone calls from search ads often get lumped into an unhelpful 'other' bucket or credited to the wrong touchpoint. Lucas and Luna break down how Google Ads call extensions and call-only ads create a data gap, why last-click phone call attribution inflates Google's role, and how a mid-market HVAC company found that 40% of…
Marketing Attribution Ignores Affiliate Link Fragmentation
Episode 126 of Marketing Analytics with Fexingo takes on one of attribution's most stubborn blind spots: affiliate link fragmentation. Lucas and Luna unpack how brands like REI and Target lose track of conversions when customers click one affiliate link but buy later via a different path, or when publishers use multiple sub-networks. They walk through real data from a 2025 affiliate audit that found 38% of commissionable conversions were never attributed to the right partner. The hosts discuss…
Why Marketing Attribution Ignores View-Through Conversions
Episode 125 of Marketing Analytics with Fexingo tackles a blind spot in most attribution setups: view-through conversions. Lucas and Luna explore how the industry's shift to last-click and click-based models systematically discounts the influence of display, video, and social ads that users see but don't click. They walk through a concrete example from a DTC brand that ran a two-month experiment comparing click-attributed revenue vs. view-through-inclusive revenue — and found that 42% of…
How Marketing Attribution Misses Trade Show Leads
Episode 124 of Marketing Analytics with Fexingo tackles a blind spot most attribution models share: trade shows and live events. Lucas and Luna dig into a 2025 B2B case — a cybersecurity firm that spent $2 million on a single conference — and trace why its attribution dashboard showed almost zero conversions, even though the sales team closed $18 million in pipeline from those handshakes. They walk through the structural problems: badge-scan data not syncing with CRM, offline conversations…
How Marketing Attribution Misses Podcast Sponsorships
Episode 123 of Marketing Analytics with Fexingo digs into why standard attribution models systematically undervalue podcast advertising. Lucas and Luna walk through a real-world example: a DTC mattress company that saw no direct-click conversions from its podcast ads, yet organic search and branded traffic spiked 40 percent within 48 hours of each episode airing. They break down three attribution blind spots — the 'headphone gap,' the 'deferred action problem,' and the 'halo effect on brand…
Why Your Attribution Model Misses Direct Mail
In this episode of Marketing Analytics with Fexingo, Lucas and Luna tackle a persistent blind spot in modern attribution: direct mail. Most marketing teams write off snail mail as unmeasurable, but new tracking methods — from QR codes to personalized URLs and machine-learning lift analysis — are proving that direct mail still drives significant conversions, especially in B2B and high-consideration purchases. Lucas shares a concrete case: a mid-size software company that ran a controlled test…
Why Your Marketing Attribution Ignores Store Visits
Lucas and Luna unpack a blind spot most attribution models share: they can't track in-store visits from digital campaigns. They walk through data from a mid-size apparel brand that ran a controlled study last quarter. After pausing Facebook and Google ads for one test region, in-store sales dropped 17 percent despite no change in online conversion rates. The hosts explain why device-level location data is still too sparse for reliable attribution, how Google's 'store visits' metric has inflated…
Why Marketing Attribution Misses Retail Media Networks
Retail media networks like Amazon Ads, Walmart Connect, and Instacart are now a $50 billion-plus ad channel, but most attribution models completely misallocate credit for these placements. In this episode, Lucas and Luna break down why last-click and multi-touch attribution both fail when a retailer owns both the ad and the transaction data — creating a closed-loop illusion that overweights the final click while ignoring upper-funnel influence from social, search, and TV. They walk through a…
How Your Attribution Model Misses Non-Click Conversions
Lucas and Luna unpack the dark matter of marketing attribution: interactions that never produce a click. They walk through a real example from a mid-market DTC brand that saw a 34 percent lift in attributed revenue after implementing a view-through window for Facebook display ads—conversions that had been invisible to last-click models. The conversation covers the mechanics of view-through attribution, the risks of over-weighting it (a well-known mattress company once over-attributed $12…
Why Marketing Attribution Overweights Facebook for B2B SaaS
In this episode of Marketing Analytics with Fexingo, Lucas and Luna unpack why Facebook attribution systematically overweights the platform for B2B SaaS companies. They walk through a real case: a $50 million ARR cybersecurity firm that saw Facebook attributed 18% of pipeline but only 2% of closed-won revenue. The hosts explain the root cause — Facebook's last-click delta window capturing low-intent clicks from employees on personal devices — and offer a fix: decouple awareness from attribution…
Why Marketing Attribution Misses Influencer Content
Lucas and Luna examine how influencer marketing breaks standard attribution models. Most platforms credit a last-click or first-touch conversion, but influencer content works differently — it builds consideration over time across multiple channels. The hosts walk through a real scenario: a beauty brand running a six-month campaign with a mid-tier influencer on Instagram. They show how the brand's attribution model credited paid search for the bulk of conversions, when the real driver was…
Why Your Attribution Model Misses Retail Media Networks
Episode 116 of Marketing Analytics with Fexingo dives into a blind spot that's quietly undermining marketing measurement: retail media networks. Lucas and Luna explore how Amazon, Walmart, and Instacart's ad platforms operate as walled gardens, capturing purchase data that traditional attribution models never see. They walk through a concrete example—a CPG brand running sponsored product ads on Amazon—and explain why last-click, first-touch, and multi-touch models all fail to account for…
Why Your Attribution Model Overweights Display Retargeting
Lucas and Luna dig into a persistent blind spot in marketing analytics: the systematic overvaluation of display retargeting by multi-touch attribution models. Using a concrete example from an e-commerce brand running a 90-day test, Lucas explains the 'proximity bias' that inflates retargeting's credit by 40-60% — because retargeting always appears last or near-last in the click path, even when upper-funnel channels like podcasts or CTV did the actual conversion work. Luna pushes back with a…
Why Your Attribution Model Overweights Facebook
Episode 114 of Marketing Analytics with Fexingo digs into a specific blind spot in digital attribution: the way platform-reported conversion data biases budgets toward Meta's ecosystem. Lucas and Luna walk through a real-world example—a DTC apparel brand spending $200,000 a month on paid social—and show how Facebook's last-click attribution overcounts its own conversions by 30 to 40 percent, silently starving channels like search and email. They explain the mechanics: the Facebook pixel…
Why Marketing Attribution Ignores Cross-Device Journeys
In episode 113 of Marketing Analytics with Fexingo, Lucas and Luna tackle one of attribution's most persistent blind spots: cross-device tracking. They explain how a single user might research a product on their phone, click an ad on a laptop, and convert on a tablet — and why most models credit the wrong touchpoint. Using a real-world example from a mid-market retailer, they show how last-click and even multi-touch models systematically undervalue mobile upper-funnel efforts. They also unpack…
Showing the latest 50 episodes. The full archive of 162 is on Apple Podcasts, Spotify and every major podcast app — or via the RSS feed above.